SARAS · Project

Robotic AI Assistant That Lets One Surgeon Do What Currently Takes Two

healthTestedTRL 5

Right now, when a surgeon operates using a robotic laparoscopic system, they always need at least one other surgeon in the room to handle the simple-but-necessary tasks — moving tissue, suctioning fluid — while the lead surgeon focuses on the main procedure. That assistant spends most of their time standing around waiting, doing something useful for only about 30% of the operation. SARAS built two robotic arms plus an AI brain that watches what the surgeon is doing in real time and steps in to handle those assistant tasks automatically. They tested the whole system on physical training models and on specially preserved human cadaver tissue to make sure it performs safely.

By the numbers

30%

Share of operation time during which the assistant surgeon performs critical tasks (idle the rest)

Consortium partners

Countries in consortium (AT, DE, ES, IT, UK)

Assistive robotic arms developed

Total project deliverables

18%

Industry partner ratio in consortium

The business problem

What needed solving

Laparoscopic robotic surgery requires multiple surgeons per operation — one to control the robot and at least one assistant to handle simple but essential tasks like tissue retraction and fluid aspiration. That assistant performs critical tasks for only 30% of the operation, meaning a highly paid expert surgeon's time is largely wasted. This inflates OR costs, ties up scarce specialist capacity, and contributes directly to longer surgical waiting lists.

The solution

What was built

The team built three robotic surgical platforms — MULTIROBOTS-SURGERY, SOLO-SURGERY, and LAPARO2.0-SURGERY — each with dedicated hardware including two robotic arms designed to hold standard laparoscopic instruments. They also built an AI cognitive supervisor that recognizes surgeon actions in real time, plans autonomous responses, and accepts voice commands, then validated the full system on phantom models and human cadaver tissue for nephrectomy and prostatectomy procedures.

Audience

Who needs this

Private hospital groups with high-volume laparoscopic robotic surgery programsMedical robotics manufacturers looking to add autonomous assistance capability to their platformsSurgical AI software companies building intraoperative decision-support toolsHealthcare systems facing surgeon shortages and long waiting lists for minimally invasive proceduresVenture-backed med-tech companies targeting the surgical robotics market

Business applications

Who can put this to work

Hospital systems and surgical centers

enterprise

Target: Private or public hospital with a robotic laparoscopic surgery program

If you run a hospital with a robotic surgery program, you currently need at least two surgeons in the OR for each laparoscopic procedure — one to operate and one to assist. This project developed two robotic assistant arms combined with an AI cognitive supervisor that monitors the operation and performs the assistant's tasks autonomously, enabling solo-surgeon procedures. The result is that one surgeon can handle cases currently requiring a full surgical team, reducing OR personnel costs and freeing expert surgeons who otherwise stand idle for the majority of an operation.

Medical robotics and surgical equipment manufacturing

mid-size

Target: Manufacturer of laparoscopic or robotic surgical platforms

If you manufacture robotic surgical systems and want to add an autonomous assistance module to your product line, this project developed and validated hardware and software architectures for three distinct surgical platforms — MULTIROBOTS-SURGERY, SOLO-SURGERY, and LAPARO2.0-SURGERY. Each includes a bilateral teleoperation architecture, force feedback, and dedicated end-effectors for standard laparoscopic tools. The systems were validated on phantom models and human cadaver tissue, giving you a pre-clinical-validated foundation to license and build upon.

Healthcare AI and surgical intelligence software

SME

Target: Health tech company building intraoperative AI or decision-support software

If you are a health tech company developing AI for operating rooms, this project built a real-time surgeon action recognition engine and cognitive supervisor that infers the current state of a surgical procedure and responds accordingly — integrated with speech recognition, situation awareness, and a hierarchical motion planner. This cognitive layer was tested in surgical simulation environments and validated on cadaver models for nephrectomy and prostatectomy. Licensing or co-developing this AI stack could accelerate your own surgical intelligence product toward clinical validation.

Frequently asked

Quick answers

What does it cost to license or implement this technology?

Based on available project data, no commercialization pricing or licensing fee information is provided in the CORDIS records. The project was funded under the Horizon 2020 RIA scheme; any business interested in licensing would need to contact the technology transfer offices of the participating universities directly.

Is this ready to deploy in a real hospital today?

Not yet. The technology has been validated on physical phantom models and Thiel soft embalmed human cadaver models for nephrectomy and prostatectomy, but no live patient clinical trials are documented in the available project data. Regulatory clearance under EU MDR Class III or FDA pathways would be required before hospital deployment.

Who owns the IP and how can it be licensed?

Based on available project data, specific IP ownership terms are not published in the CORDIS records. In Horizon 2020 RIA projects, IP typically belongs to the contributing partners — here that means negotiating with the University of Verona and up to 10 other consortium members across 5 countries, likely through their respective tech transfer offices.

What regulatory approvals are needed before this can be sold?

Autonomous surgical robots are classified as Class III medical devices under EU MDR 2017/745, requiring clinical evidence, a notified body review, and CE marking before market entry. Based on available project data, no regulatory submissions or clinical trial registrations are mentioned, meaning this critical step lies ahead for any commercializing partner.

How much surgical time could this technology recover?

The project objective states that the assistant surgeon performs critical tasks for only 30% of the operation time and stands waiting the rest. Automating that assistant role means the expert surgeon's time currently consumed by waiting can be redirected to additional cases, directly expanding hospital throughput without increasing headcount.

Can this integrate with existing surgical robots on the market?

The robotic arms were designed to hold and operate standard off-the-shelf laparoscopic instruments, which suggests compatibility with existing tool ecosystems. Based on available project data, direct integration testing with specific commercial platforms is not documented.

Are there industry partners already involved in the consortium?

Yes — the 11-partner consortium includes 2 industry partners and 2 SMEs (18% industry ratio) across 5 countries. This indicates commercial interest during the research phase, though specific company names and commercial commitments are not detailed in the available CORDIS data.

Consortium

Who built it

The SARAS consortium brought together 11 partners from 5 countries (Austria, Germany, Spain, Italy, UK), coordinated by the University of Verona. The makeup is heavily academic — 7 universities and 1 research institute account for 73% of partners — with only 2 industry partners and 2 SMEs making up the 18% industry ratio. This is a typical composition for deep-engineering research: strong scientific and technical depth, but limited built-in commercialization infrastructure. For a business evaluating licensing or co-development, this structure means IP negotiations will likely involve multiple university technology transfer offices simultaneously, and any commercializing partner would need to own the regulatory strategy, clinical validation pathway, and go-to-market execution themselves.

UNIVERSITA DEGLI STUDI DI VERONACoordinator · IT
UNIVERSITY OF DUNDEEparticipant · UK
FONDAZIONE CENTRO SAN RAFFAELEthirdparty · IT
UNIVERSITAT POLITECNICA DE CATALUNYAparticipant · ES
OSPEDALE SAN RAFFAELE SRLparticipant · IT
OXFORD BROOKES UNIVERSITYparticipant · UK
ACMIT GMBHparticipant · AT
UNIVERSITA DEGLI STUDI DI MODENA E REGGIO EMILIAparticipant · IT
UNIVERSITA DEGLI STUDI DI FERRARAparticipant · IT
UNIVERSITA VITA-SALUTE SAN RAFFAELEthirdparty · IT

How to reach the team

Contact the technology transfer office at UNIVERSITA DEGLI STUDI DI VERONA (Italy) — the project coordinator — to explore licensing or collaboration opportunities.

Order a report on this consortium See UNIVERSITA DEGLI STUDI DI VERONA profile →

Next steps

Talk to the team behind this work.

SciTransfer can connect you with the SARAS research team to discuss licensing, co-development, or a joint clinical validation project. Contact us for a one-page brief and a warm introduction to the right person.

Order a report on this topic More in Health & Biomedical